The automotive industry is increasingly focused on developing lightweight, fuel-efficient, and structurally robust components to meet stringent performance and sustainability requirements. Additively manufactured lattice structures have emerged as a promising solution due to their high strength-to-weight ratio, energy absorption capability, and geo...

By Sapna Bawankar, Priya Vij

This research paper examines how the strategic marketing analytics, which combines big data, artificial intelligence (AI), and knowledge management can be used to improve the competitive advantage in data-driven markets. The research tests the effectiveness of AI-driven analytics in enhancing the performance of the market, customer high retention a...

By M. Venith Vijay, Vijayakanthan Selvaraj, R. Muzhumathi, P. Sundara BalaMurugan

The study will be conducted to complement the diagnosis of proximal caries lesions that are difficult to improve due to their location between the teeth, as shown in Near-Infrared Light Transillumination (NILT) photographs. It was proposed to enhance caries detection with a semantic segmentation model based on YOLOv11, which is more specific in det...

By Asma Alatawi, Wdaee Alhalabi, Hani Nassar, Arwa Basbrain, Hattan Jamalellail, Mohammed Alsadat

Sentiment analysis (SA) is important in comprehending the opinions and online discussions of people in different languages, particularly in high-resource and low-resource languages. In the present paper, a new model of transfer deep learning is presented, which incorporates cross-lingual embeddings in an attempt to boost sentiment analysis in both ...

By Jayaprakash Vattikundala, M. Siva Ganga Prasad

Nanoscience and nanotechnology transformed material science with the introduction of nanomaterials that have special physical, chemical, optical, and mechanical characteristics because of their tiny size on the nanoscale. The materials have superior surface areas, quantum imagery, and unique electrical properties when compared to bulk materials, wh...

By Anil Kumar, Swati, Niharika

The innovation of Machine Learning (ML) techniques is evolving from basic techniques to optimized techniques, considerably improving the performance of prediction models. In the proposed work, the study primarily explores fundamental ML classification methods to classify banking customers based on their credit information. The classification of cus...

By Sufaira Shamsudeen, K. Ranjith Singh

To solve the problems of traditional Apriori algorithm in power marketing big data processing, such as candidate item set redundancy, low single-machine computing efficiency, and difficulty in adapting to multi-dimensional time series data, this study proposes an improved Apriori algorithm that integrates Resilient Distributed Dataset (RDD) distrib...

By Fan Pan, Lingen Zhou, Lu Gan, Wei Kang, Xiaolei Li

The stability of smart grids (SG) plays a critical role in improving the stability of power supply, particularly when system failures or sensor breakdowns could occur and result in a lack of input data. This paper provides a new method of prediction of smart grid consistency by using a Gradient Policy prediction model, which is based on reinforceme...

By S. Mahendran, B. Gomathy

It presents a dynamic model of inventory management of the deteriorating items with time-sensitive demand and variable holding costs. The model is used to solve the problem in industries where demand is seasonal or because of other external conditions, like weather or market conditions. A two-tier inventory model is implemented as a way of minimizi...

By Prashant Sharma, Birendra Kumar Chauhan, Gajraj Singh

Rapid and accurate assessment of civic infrastructure following a natural or artificial disaster is essential to planning emergency response and recovery. This paper introduces a control system based on deep reinforcement learning (DRL) to coordinate unmanned aerial vehicle (UAV) swarms and methodically approach the post-disaster infrastructure ins...

By Moti Ranjan Tandi, Archana Mishra